Data Scientist, Geospatial

Neara

. Collaborate directly with customer geospatial and GIS teams in a hybrid setting .

Posted 10/14/2026full-timeHouston • Texas • United StatesMid-LevelSenior💰 $140,000 - $160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building predictive risk models using LiDAR and terrain data, while effectively collaborating with geospatial teams to deliver data-driven insights for utility capital investments. Proven ability to mentor others in data analytics and maintain spatial data pipelines for diverse geospatial formats.

Highest-signal resume keywords

Predictive Risk ModelingGeospatial Data AnalysisData Pipeline DevelopmentQA/QC Benchmark EstablishmentCustomer Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceMachine LearningLiDARSpatial Data IntegrationData AnalyticsQuantitative AnalysisCRS TransformationsModel TrainingVectorizationPredictive Modeling

Soft Skills

Excellent CommunicationNatural CollaborationSelf-DrivenOwnership of ProjectsAdaptability

Industry Keywords

GeospatialPower GridData WorkflowsSpatial ChallengesWildfire Risk PreventionHigh-Growth TechnologyHybrid Work EnvironmentData-Driven InsightsBusiness-Driven OutcomesFast-Paced Environments

About the role

Key responsibilities & impact

Collaborate directly with customer geospatial and GIS teams in a hybrid setting
Spend time on-site at customer offices to understand data workflows, integrate systems, and solve spatial challenges
Build predictive risk models on Neara using LiDAR, terrain models, and weather data
Simulate conductor sag, sway, and vegetation fall-in risks to prevent wildfire ignitions
Translate spatial and structural risk metrics into data-driven insights for utility capital investment decisions
Build and maintain spatial data pipelines to ingest, clean, vectorize, and integrate diverse geospatial data formats
Establish QA/QC benchmarks for spatial accuracy, CRS transformations, and structural alignment
Mentor others in model training, data analytics, and data-driven product development

Requirements

What you’ll need

5+ years of hands-on experience in data science or machine learning
Geospatial data or power grid domain experience is a plus
Strong quantitative intuition for data
Excellent communication skills
Proven experience presenting complex findings to customers and senior leaders
Experience working in fast-paced, high-growth scale-up technology environments is a plus
Self-driven with a bias for action
Comfortable taking full ownership of complex projects and adapting quickly to shifting priorities
Natural collaborator across technical teams and external customer stakeholders
Track record of navigating messy, real-world datasets to deliver clear, business-driven outcomes
Ability to work in a hybrid setting and spend time on-site at customer offices

Benefits

Comp & perks

Significant equity component
Work with an industry-leading, multi-modal spatial data stack
Opportunity to solve real-world engineering challenges at immense scale
Spatial modeling directly mitigating wildfire risks and hardening critical infrastructure
Opportunity to shape the spatial architecture of the core product line
Collaboration with top-tier ML and software engineers